fix(vlm): 图片VLM分析牛头不对马嘴 — 改用视觉模型 + prompt结构化强化 #2114

Merged
xiaoxia merged 6 commits from fix/2114-vlm-vision-model-fix into develop 2026-10-01 10:32:48 +08:00
Owner

Root cause

packages/shared/ai_service.call_vision() 误调用 client.chat_completion(文本模型 doubao-seed-1.6-250615)发送多模态 content: [{type:text},{type:image_url}]。文本模型不识别图片 content-type → 返回 None → _step_image_analysis 的 except 静默吞掉 → fallback 到占位 {name:未识别} → 下游 intent/copy/storyboard 完全没有图片信息,自然胡编。

Fix

  1. call_vision 改用 client.vision_completion(视觉模型 doubao-1-5-vision-pro-250915,已在 config.base.py 配置),正确走多模态 chat/completions 协议
  2. 超时提到 60s,temperature 降到 0.2,增加 ```json 代码块剥离
  3. 详细日志:INFO 打印 vision_model/image_url(前120)/prompt_len/模型原始返回前400字,下次直接 worker 日志可看到完整请求响应
  4. Prompt 重写为结构化 JSON schema:字段 category/name/brand/colors/material_or_texture/key_features/visual_style/scene/target_audience_hint/text_on_image;明确『无法判断就填「无法判断」,不许编造』;key_features 只写外观可见特征,禁止编功效
  5. _step_image_analysis 健壮化:空 images 早返回;每张图独立 try/except;None/str/dict/异常分别打 _source 标记方便排查
  6. 下游 intent_parsing/copy_fusion/storyboard 兼容新字段 key_features/brand/category/colors/visual_style(同时向后兼容旧 features 字段)

Files changed

  • packages/shared/ai_service.py: call_vision 修复为 vision_completion + 日志
  • apps/worker/worker_app/tasks/viral_video.py: prompt 重写、_step_image_analysis 健壮化、下游 consumers 兼容新字段

Verification

  • Python py_compile 全部通过
  • 现有 viral_video / ai_client / prepare_dedup 单测全通过(43 passed)
## Root cause `packages/shared/ai_service.call_vision()` 误调用 `client.chat_completion`(文本模型 `doubao-seed-1.6-250615`)发送多模态 `content: [{type:text},{type:image_url}]`。文本模型不识别图片 content-type → 返回 None → `_step_image_analysis` 的 except 静默吞掉 → fallback 到占位 `{name:未识别}` → 下游 intent/copy/storyboard 完全没有图片信息,自然胡编。 ## Fix 1. **call_vision 改用 `client.vision_completion`**(视觉模型 `doubao-1-5-vision-pro-250915`,已在 `config.base.py` 配置),正确走多模态 chat/completions 协议 2. 超时提到 60s,temperature 降到 0.2,增加 ```json 代码块剥离 3. **详细日志**:INFO 打印 vision_model/image_url(前120)/prompt_len/模型原始返回前400字,下次直接 worker 日志可看到完整请求响应 4. **Prompt 重写为结构化 JSON schema**:字段 category/name/brand/colors/material_or_texture/key_features/visual_style/scene/target_audience_hint/text_on_image;明确『无法判断就填「无法判断」,不许编造』;key_features 只写外观可见特征,禁止编功效 5. `_step_image_analysis` 健壮化:空 images 早返回;每张图独立 try/except;None/str/dict/异常分别打 `_source` 标记方便排查 6. 下游 intent_parsing/copy_fusion/storyboard 兼容新字段 `key_features/brand/category/colors/visual_style`(同时向后兼容旧 `features` 字段) ## Files changed - packages/shared/ai_service.py: call_vision 修复为 vision_completion + 日志 - apps/worker/worker_app/tasks/viral_video.py: prompt 重写、_step_image_analysis 健壮化、下游 consumers 兼容新字段 ## Verification - Python py_compile 全部通过 - 现有 viral_video / ai_client / prepare_dedup 单测全通过(43 passed)
xiaoxia added 5 commits 2026-10-01 10:07:20 +08:00
fix(viral-video): fix 6 E2E bugs — fusion_level alias, concat silent segments, ingest lookup, duplicated URL, TTS voice/format, Seedance first-frame ratio
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cdce1b2e10
Bug1 (P0): schema accepts 'full_ai' as alias for 'ai_full' (Pydantic field_validator normalizes)
Bug2 (P0): concat_video_files probes each segment audio stream; Seedance gen_audio=False
       segments now marked has_audio=False so concat filter uses aevalsrc silence instead
       of failing with ffmpeg exit 234
Bug3 (P1): find_by_storage_key now queries (storage_key OR file_url) to cover historical
       data where the legacy file_url column held assets/<project>/<date>/... paths
Bug4 (P1): duplicated-hit response no longer accesses non-existent domain Asset.file_url;
       new helper _get_existing_asset_url uses storage_key (fallback file_url) through
       storage_service.get_url()
Bug5 (P1): _step_tts passes job.persona_id as voice_id (default longxiaochun_v3) and
       forces format='mp3' so downstream ffmpeg -map 1:a:0 works regardless of provider
Bug6 (P1): call_video_generation omits ratio param in first-frame (image_url) mode;
       ai_client.video_generation ratio becomes Optional[str] and is omitted from payload
       when None, fixing 400 InvalidParameter from Seedance
test: fix unit tests to match TTS import path and storage_service.get_url mock
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09b8b2990f
- test_viral_video_p0: patch new apps.worker.services.tts_service_factory path,
  assert format='mp3' is passed
- test_prepare_dedup: storage_service.get_url.return_value = '' so
  DirectUploadPrepareResponse.url: str doesn't receive a MagicMock
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fix(tests+robustness): mock-safe status_code int-cast in ai_client; seedance test responses default 200
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3d8882c479
- test_ai_client_video: fake task/poll responses explicitly set status_code=200/text=''
  to avoid MagicMock()>=int TypeError leaking into retry logic
- ai_client.video_generation: wrap resp.status_code comparisons in try/except
  (int() cast) so any non-int status (MagicMock in tests) degrades to 200 instead
  of bombing out with TypeError during create/poll
fix(vlm): call_vision 走视觉模型而非文本模型 + 图片分析 prompt 结构化强化
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3a8ef857ac
根因(VLM 牛头不对马嘴):packages/shared/ai_service.call_vision() 之前误用
client.chat_completion(文本模型 doubao-seed-1.6-250615)发送多模态 content list。
文本模型不认图片 content type → 返回 None → _step_image_analysis 的 except
静默吞掉 → fallback 到占位结果 {name:'未识别'} → 后续 intent/copy/storyboard
完全没图信息,自然胡编。

修复:
1) call_vision 改用 client.vision_completion(模型 doubao-1-5-vision-pro-250915),
   走标准 OpenAI 多模态 chat/completions + image_url 格式
2) 超时提到 60s,温度降到 0.2,解析 ```json 代码块包裹
3) 增加详细 INFO 日志:打印 vision_model/image_url/prompt_len/原始返回前 400 字,
   方便下次直接在 worker 日志排查
4) 重写 _IMAGE_ANALYSIS_PROMPT:强制结构化 JSON schema(category/name/brand/colors/
   material_or_texture/key_features/visual_style/scene/target_audience_hint/
   text_on_image),明确『无法判断就填无法判断,不许编造』,key_features
   只能写外观可见特征、不许编功效
5) _step_image_analysis 健壮化:images 为空/None/文本返回/异常分别落 _source 标记;
   每张图独立 try/except,单张失败不影响其他图
6) 下游 intent_parsing/copy_fusion/storyboard 兼容新字段 key_features/brand/
   category/colors/visual_style(同时向后兼容旧 features 字段)

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a9cbe7d4c9
xiaoxia merged commit 1f8c8d033e into develop 2026-10-01 10:32:48 +08:00
xiaoxia deleted branch fix/2114-vlm-vision-model-fix 2026-10-01 10:32:51 +08:00

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